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Martin Cusack,1 Hamish W. King,2 Paolo Spingardi,1 Benedikt M. Kessler,3 Robert J. Klose,2 and Skirmantas Kriaucionis1 1Ludwig Institute for Cancer Research, University of Oxford, Oxford, OX3 7DQ, United Kingdom; 2Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, United Kingdom; 3Target Discovery Institute, University of Oxford, Oxford, OX3 7FZ, United Kingdom
Epigenetic modifications on chromatin play important roles in regulating gene expression. Although chromatin states are often governed by multilayered structure, how individual pathways contribute to gene expression remains poorly under- stood. For example, DNA methylation is known to regulate transcription factor binding but also to recruit methyl-CpG binding proteins that affect chromatin structure through the activity of histone deacetylase complexes (HDACs). Both of these mechanisms can potentially affect gene expression, but the importance of each, and whether these activities are inte- grated to achieve appropriate gene regulation, remains largely unknown. To address this important question, we measured gene expression, chromatin accessibility, and transcription factor occupancy in wild-type or DNA methylation-deficient mouse embryonic stem cells following HDAC inhibition. We observe widespread increases in chromatin accessibility at ret- rotransposons when HDACs are inhibited, and this is magnified when cells also lack DNA methylation. A subset of these elements has elevated binding of the YY1 and GABPA transcription factors and increased expression. The pronounced ad- ditive effect of HDAC inhibition in DNA methylation–deficient cells demonstrates that DNA methylation and histone deacetylation act largely independently to suppress transcription factor binding and gene expression.
[Supplemental material is available for this article.] The most abundant DNA modification in mammals is 5-methylcy- ylation is reduced or absent (Domcke et al. 2015; Maurano et al. tosine (5mC) which is found predominantly within CpG dinucle- 2015; Yin et al. 2017). otides (Lister et al. 2009; Stadler et al. 2011). DNA methylation is In addition to directly altering the binding of transcription deposited and maintained through the concerted activity of three factors, methylated CpG is recognized by methyl binding essential DNA methyltransferases (DNMT1, DNMT3A, DNMT3B) domain-containing (MBD) and zinc-finger methyl-cytosine bind- (Goll and Bestor 2005) and plays important roles in transcriptional ing proteins (Hendrich and Bird 1998; Lopes et al. 2008; Quenne- repression. For example, DNA methylation is known to regulate ville et al. 2011). MBD proteins interact with histone deacetylase imprinted genes (Kaneda et al. 2004), some tissue-restricted genes (HDAC) enzymes and promote the formation of transcriptionally (De Smet et al. 1999; Maatouk et al. 2006; Borgel et al. 2010), evo- repressive chromatin environments (Nan et al. 1998; Zhang et al. lutionarily young retrotransposons (Davis et al. 1989; Walsh et al. 1999; Kokura et al. 2001; Yoon et al. 2003) via the removal of acetyl 1998; Castro-Diaz et al. 2014), genes on the inactive X groups from lysine residues in histones. Chromosome (Beard et al. 1995; Hansen et al. 1996), and certain Despite the active recruitment of HDACs to methylated tumor suppressor genes in cancer cells (Toyota et al. 1999; Rhee CpGs, the extent to which DNA methylation relies on HDAC activ- et al. 2002; Robert et al. 2003). ity to affect gene expression is still poorly understood. HDAC inhi- Although 60%–80% of CpGs in the genome are methylated, bition, or disruption of the interaction between MBD proteins and DNA methylation is absent or reduced in regions bound by tran- the HDAC-containing complexes, has been shown to alleviate scription factors such as in CpG islands, gene promoters, and distal transcriptional silencing mediated by DNA methylation in report- regulatory elements (Stadler et al. 2011; Hon et al. 2013; Ziller et al. er gene assays (Jones et al. 1998; Nan et al. 1998; Ng et al. 1999; 2013). This observation led to the proposal that DNA methylation Lyst et al. 2013). Nevertheless, at other endogenous genes, inhib- may limit transcription factor occupancy. In support of this mod- iting HDACs did not recapitulate the effects on gene expression el, in vitro experiments have revealed that 5mC can affect the af- that manifest when DNA methylation is removed (Cameron finity of most DNA-binding proteins that contain CpG et al. 1999; Coffee et al. 1999; Brunmeir et al. 2010; Reichmann dinucleotides in their binding motif (Hu et al. 2013; Spruijt et al. et al. 2012). Therefore, although it is clear that DNA methylation 2013; Kribelbauer et al. 2017; Yin et al. 2017). Furthermore, certain is capable of altering TF-DNA interactions and recruiting HDACs, transcription factors (TFs), including NRF1 and CTCF, have been how these distinct mechanisms contribute to DNA methylation- shown to have altered binding profiles in cells where DNA meth- dependent repression at the genome scale remains unknown.
Corresponding author: [email protected] Article published online before print. Article, supplemental material, and publi- © 2020 Cusack et al. This article, published in Genome Research, is available cation date are at http://www.genome.org/cgi/doi/10.1101/gr.257576.119. under a Creative Commons License (Attribution-NonCommercial 4.0 Interna- Freely available online through the Genome Research Open Access option. tional), as described at http://creativecommons.org/licenses/by-nc/4.0/.
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Cusack et al.
Failure to inactivate transcription and mobility of retrotrans- (Supplemental Fig. S1A) but yielded a robust increase in global his- posons has been linked to genome instability in cancer (Carreira tone acetylation as detected by immunoblotting (Fig. 1B). There et al. 2014; Tubio et al. 2014; Scott and Devine 2017; Schauer were no significant changes in global 5mC levels between TSA- et al. 2018) and the manifestation of neurological diseases and DMSO (solvent)-treated cells (Supplemental Fig. S1B). (Coufal et al. 2011). DNA methylation is an important contributor To examine histone acetylation in more detail, we performed to silencing of retrotransposons, where it acts in concert with his- native calibrated ChIP-seq for acetylated histone H3 (H3ac). TSA tone deacetylation and histone (H3K9) methylation (Bourc’his treatment led to a global increase in H3ac in wild-type and and Bestor 2004; Karimi et al. 2011; Rowe et al. 2013; Sharif DNMT.TKO cells both at previously hyperacetylated sites (ChIP- et al. 2016). Whether chromatin mechanisms are redundant or col- seq peaks) and the remaining genomic space (Fig. 1C–E; Supple- laborative while acting on different classes of retrotransposons is mental Fig. S1C). The increase in histone acetylation at repetitive incompletely understood. regions and unannotated genomic loci following HDAC inhibi- In this study, we aimed to determine individual and collabo- tion was greater in DNMT.TKO compared to wild-type cells (Fig. rative roles of DNA methylation and HDAC activity. To this pur- 1E). This observation coincides with high DNA methylation levels pose, we disrupted both processes, one at a time or in in the aforementioned regions in WT cells, whereas hyperacety- combination, in mouse embryonic stem cells and measured the lated sites contain low median DNA methylation (Supplemental impact on chromatin accessibility, transcription factor occupancy, Fig. S1D). This additive effect of DNA methylation loss and and gene regulation. HDAC inhibition on histone acetylation in these regions could be explained by enhanced recruitment of histone acetyltransfer- ases (HATs), potentiated by DNA-binding proteins with specificity Results to unmodified CpGs (e.g., CxxC-domain proteins). Alternatively, the lack of DNA methylation may disrupt the recruitment of Disruption of HDAC activity and DNA methylation in mouse HDACs by MBD-domain proteins, resulting in a lower capacity embryonic stem cells for compensatory mechanisms to deacetylate histones or prevent To determine the contribution of DNA methylation and the activity histone acetylation. of HDAC enzymes on transcriptional regulation, we treated wild- In summary, HDAC inhibition using TSA induces histone type (J1) or Dnmt3a/Dnmt3b/Dnmt1 triple knockout (DNMT.TKO) acetylation broadly across the genome with no detectable change mouse embryonic stem cells (Tsumura et al. 2006) with the HDAC in DNA methylation, enabling us to evaluate the extent and the inhibitor trichostatin A (TSA) (Fig. 1A). The chosen dose of TSA mode by which these two mechanisms contribute to chromatin had minimal effects on the morphology or cell cycle of mESCs function.
Figure 1. Disruption of HDAC activity and DNA methylation in mouse embryonic stem cells. (A) Schematic of the experimental approach used in this study. (B) Immunoblot analysis of global histone H3 and H4 acetylation levels after 36-h TSA treatment in mESCs. Samples were derived from three bio- logical replicate experiments. (C) Representative snapshot of genomic region showing H3ac ChIP-seq read coverage calibrated to the spike-in galGal4 ge- nome. (D) Metaplot showing the average calibrated H3ac ChIP-seq signal from DMSO- or TSA-treated wild-type and DNMT.TKO cells in 10-kb regions surrounding the center of ChIP-seq peaks (n = 28608). (E) Distribution of H3ac ChIP-seq reads within genomic intervals separated into three mutually ex- clusive categories. For every sample, the number of mm10 reads overlapping each category was divided by the total number of reads mapping to the galGal4 genome. Data are represented as the mean; points indicate the values for two biological replicates.
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DNA methylation and HDAC activity have distinct contributions the most enriched, consistent with the findings of Domcke et al. to the chromatin accessibility landscape (2015) (Supplemental Fig. S2J; Supplemental Table S5). Similar to their results, sequence motifs recognized by the NFY complex, To compare the impact of DNA methylation and histone acetyla- ETS and basic Helix-Loop-Helix (bHLH) transcription factors tion on chromatin function, we profiled chromatin accessibility were also enriched in DNMT.TKO THSs. In vitro affinity measure- in wild-type and DNMT.TKO cells in the absence or presence of ments and locus-specific ChIP evidence suggest that the binding of TSA using ATAC-seq (Fig. 1A). these transcription factors to their cognate recognition sites is sen- Employing this data, we first defined a set of 83,395 transpo- sitive to DNA methylation (Hu et al. 2017; Yin et al. 2017), sup- sase hypersensitive sites (THSs) that were called as significantly ac- porting the idea that accessibility gains occur in the absence of cessible in at least one experimental condition. Sample-to-sample DNA methylation due to unimpeded binding of these proteins. correlations and a principle component analysis both clustered bi- We next examined the effects of HDAC inhibition on the ological replicate samples together, demonstrating that treatment chromatin accessibility landscape of wild-type and DNMT.TKO and genotype induced reproducible changes in accessibility mES cells. Few loci displayed significant accessibility gains in (Supplemental Fig. S2A–C). We identified THSs that display differ- TSA- versus DMSO-treated cells, relative to the numbers identified ential accessibility by examining the effect of DNA methylation when comparing DNMT.TKO to WT. In fact, we observed that the loss, or that of HDAC inhibition in either wild-type or DNA meth- vast majority of regions display reduced accessibility in cells upon ylation-deficient cells (Fig. 2A). In all comparisons, regions that HDAC inhibition, in both WT and DNMT.TKO cells (Fig. 2A; gained accessibility had a lower CpG and GC content than un- Supplemental Fig. S2H). The effect was more pronounced in cells changed ones, which was related to the reduced presence of differ- depleted of DNA methylation, in which 38% of all THSs showed ential THSs at promoters (Supplemental Fig. S2D–G). a significant reduction in ATAC-seq signal when treated with We first focused on comparing DNMT.TKO to WT DMSO- TSA. Congruently, THSs in TSA-treated cells are smaller, as seen treated cells in order to characterize the chromatin accessibility when aggregating the signal across all THSs or at individual sites changes that occur following the loss of 5mC. We identified in the genome (Fig. 2B,C). We further noted that genome accessi- 6427 THS regions that significantly gained accessibility and 7135 bility changes at THSs were similar between TSA-treated WT and that significantly lost accessibility in the absence of DNA methyl- DNMT.TKO cell lines (Spearman’s correlation coefficient = 0.649) ation (Fig. 2A, left). Significant increases in ATAC-seq signal (Fig. 2D). In contrast, there was a considerable discrepancy in the occurred preferentially at loci that showed low accessibility in changes occurring with either DNA methylation loss or TSA treat- wild-type cells, whereas significant decreases were more broadly ment (Spearman’s correlation coefficient = 0.187) (Fig. 2E). detected at regions with intermediate levels of wild-type accessibil- Consequently, the main difference in the response to HDAC inhi- ity, a finding that was consistent when using more stringent FDR bition in either the presence or absence of DNA methylation is the thresholds for calling significant differences (Supplemental Fig. magnitude of the changes. S2H). Differential THS regions account for ∼16% of all sites that We then examined the relationship between TSA-induced were detected as being accessible in wild-type or DNMT.TKO changes in H3 acetylation and genome accessibility (Supplemen- mES cells when using a FDR threshold of 0.01, demonstrating tal Fig. S3A). THSs which lose or display no change after TSA treat- that DNA methylation has an important role in maintaining acces- ment had similar gains in H3 acetylation, whereas THSs which sibility patterns. However, complete loss of DNA methylation in gained accessibility demonstrated elevated acetylation (Supple- mouse ES cells does not produce widespread alterations, in agree- mental Fig. S3A, bottom panel). Discordance between loss of acces- ment with similar results obtained using DNase-seq (Domcke sibility and H3 acetylation prompted us to examine the possibility et al. 2015). that the observed loss of accessibility might be an indirect effect To assess the fraction of differential accessibility events that and subject to a different interpretation. Reduced signal at THS in- occur as a direct consequence of a loss in DNA methylation, we tervals in TSA-treated samples indicates that DNA fragments orig- made use of public whole-genome bisulfite sequencing (WGBS) inating from these regions are underrepresented as a fraction of the data generated from E14 mESCs grown under the same growth entire ATAC-seq library, relative to their fraction in untreated sam- conditions (Habibi et al. 2013). Similar to previous observations ples. Concurrently, a larger proportion of fragments mapping to (Domcke et al. 2015), we found that gains in accessibility in the inaccessible compartment of the genome (i.e., the back- DNMT.TKO cells frequently occur at regions that are methylated ground) are sequenced. We envision two possible explanations in WT cells (Supplemental Fig. S2I, top right quadrant). Specifi- for this observed reduction of ATAC-seq signal at THS intervals. cally, 56% of DNMT.TKO loci that significantly gain in accessibil- The first possibility is that, upon TSA treatment, chromatin ity have a mean methylation value above 60% in WT cells accessibility is reduced at THSs, meaning that fewer reads would (Supplemental Fig. S2I). These represent loci at which DNA meth- be obtained from within these intervals. As a consequence of se- ylation is likely to play a role in restraining the formation of a Tn5 quencing a fixed number of DNA fragments, we would thus ob- accessible state, potentially through interference with transcrip- serve a relative increase in accessibility signal from the genomic tion factor binding. On the other hand, the relationship between compartment outside THSs (the “inaccessible” compartment). accessibility reduction in DNMT.TKO cells and DNA methylation According to this hypothesis, the additional reads sequenced is less straightforward (Supplemental Fig. S2I). Only 2.8% of the re- from the inaccessible compartment would be distributed evenly gions displaying significantly reduced accessibility in DNMT.TKO throughout the remaining genomic space. The second possibility cells have high levels of methylation in wild-type cells (≥60% is that TSA treatment results in elevated accessibility in genomic re- methylation), making it more difficult to attribute these differenc- gions outside of THSs. The relative reduction in the ATAC-seq sig- es in chromatin accessibility to changes in methylation. nal at THSs then becomes a secondary consequence of elevated Screening a collection of 264 known vertebrate transcription accessibility outside THSs. This scenario would be supported if factor motifs (HOMER database) (Heinz et al. 2010) for enrichment we were to identify an enrichment in accessibility at particular sub- at DNMT.TKO-specific THSs, we identified the NRF1 motif as being divisions of the inaccessible compartment.
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Figure 2. DNA methylation and HDAC activity have distinct contributions to the chromatin accessibility landscape. (A) Volcano plots representing the false discovery rate (FDR) and fold change values obtained through pairwise differential analyses of ATAC-seq signal at 83,395 THSs. Regions with signifi- cantly differential accessibility are shown in red on the scatterplots and their numbers are summarized in the form of pie charts (light blue = significant decrease; red = significant increase). (B) Metaplot showing the average ATAC-seq signal from DMSO- or TSA-treated wild-type and DNMT.TKO cells in 4-kb regions surrounding the center of THSs (n = 83,395). (C) Representative UCSC Genome Browser snapshot showing CpG methylation levels and ATAC-seq read coverage. (D) Scatterplot comparing the fold change in ATAC-seq signal following TSA treatment in DNMT.TKO versus wild-type cells. (E) Scatterplot comparing the fold change in ATAC-seq signal after loss of DNA methylation versus the change seen following TSA treatment in wild- type cells at 83,395 THSs. In D and E, the dashed line has a slope of 1 and intercept of 0. Colors indicate density of points per graph area. SCC = Spearman’s correlation coefficient. (F) Box plots summarizing the percentage of reads from each ATAC-seq library that map to intervals split into three mutually exclusive categories. Two-tailed Student’s t-tests; (∗) P-value < 0.05, (∗∗) P-value < 0.01, (ns) nonsignificant (P-value > 0.05). (G) Box plots summa- rizing the distribution of reads from each ATAC-seq library that map to intervals split into three mutually exclusive categories, relative to the distribution expected by chance, that is, if non-THS reads were shuffled randomly within the genomic space outside of THSs. Values shown in F are divided by those in Supplemental Figure S3B.(H) Distribution of ATAC-seq reads across different classes of repetitive elements as a percentage of the total library size. Data are represented as mean + SD. Two-tailed Student’s t-tests; (∗) P-value < 0.05, (∗∗) P-value < 0.01, nonsignificant differences are not indicated.
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To explore the above-mentioned interpretations, we calculat- S2J, S3I). Elevated chromatin accessibility may be a result of abnor- ed the fraction of reads in the ATAC-seq libraries that overlapped mal TF binding (Domcke et al. 2015; Maurano et al. 2015); howev- with three categories of genomic regions: transposase hyperacces- er, it is not known whether our chromatin perturbations cause sible regions (THSs, 83,395 intervals covering 55 Mb, 2.03% of the more widespread TF binding without inducing transposase hyper- mm10 genome); genomic intervals consisting of repetitive ele- sensitivity. Thus, we decided to directly measure how DNA meth- ments (RepMask intervals, excluding sequences that overlap ylation and histone acetylation affect the genomic distribution of THSs, 1.19 Gb, 43.39% of mm10 genome); and the remaining ge- selected transcription factors. We performed ChIP-seq in WT and nomic space (unannotated regions, 54.58%) (Fig. 2F). This analysis DNMT.TKO mESCs in the presence or absence of TSA, to map shows that gains in accessibility in TSA-treated samples occur pref- the genome-wide occupancy of five transcription factors erentially at repetitive elements compared to unannotated regions (GABPA, MAX, NRF1, SP1, and YY1) that possess distinct DNA- (Fig. 2F), supporting a contribution from the second scenario out- binding domains and are known to bind cognate sequences con- lined above. The increase in coverage observed at repeats is larger taining CpG dinucleotides (Fig. 3A). than that obtained if the same number of non-THS sequencing We identified 4735, 19,236, 3102, 6666, and 6055 regions as reads are randomly shuffled into the combined “RepMask” and being reproducibly occupied by GABPA, MAX, NRF1, SP1, and YY1 unannotated genomic compartments (Fig. 2F; Supplemental Fig. in at least one experimental condition, respectively (Supplemental S3B,C). Furthermore, the distinct accessibility changes observed Table S2). Biological replicates clustered together (Supplemental at repeat regions are unlikely to be solely a consequence of differ- Fig. S4A) and the DNA motifs known to be bound by these tran- ences in the induction of histone acetylation, as the H3ac levels scription factors were the most highly enriched within the identi- in both compartments are equivalent following HDAC inhibition fied ChIP-seq peaks relative to the entire collection of motifs in the (Supplemental Fig. S3D). These results argue against the first pro- HOMER database, providing assurance of the specificity of these posed mechanism being responsible for the reduction in ATAC- ChIP assays (Supplemental Fig. S4B). Moreover GABPA, NRF1, seq signal at THSs in TSA-treated samples. Rather, our findings sug- SP1, and YY1 protein abundance is not substantially affected in gest that genome-wide hyperacetylation following HDAC inhibi- our examined conditions (Supplemental Fig. S4C). A small reduc- tion encourages gains in accessibility at repeat elements. tion of SP1 and NRF1 is observed after treatment with TSA; howev- Although gains in accessibility occur preferentially at repetitive el- er, this would not be able to explain the predominant gains in ements in TSA-treated cells, any additional increase in accessibility occupancy of these TFs (Fig. 3B). globally cannot be excluded using our experimental setup. For all five transcription factors, loss of DNA methylation or We next subdivided the repeat regions further by examining HDAC inhibition resulted in increased transcription factor the changes in accessibility occurring at various classes of repeti- occupancy (Fig. 3B). However, the relative impact of these two al- tive elements (Fig. 2H). We found that the fraction of reads map- terations varied depending on the individual protein. In accor- ping to LINE and LTR elements increased upon TSA treatment, dance with our ATAC-seq analysis (Supplemental Fig. S2J), NRF1 although this was significant in DNMT.TKO but not in WT cells. gained novel binding sites in DNMT.TKO compared to wild-type Differential analysis of the ATAC-seq coverage between samples re- cells (Fig. 3B). As these regions are methylated in wild-type cells vealed that there were significant increases in the number of (Fig. 4A), this suggests that DNA methylation restricts NRF1 bind- ATAC-seq reads mapping to 33 of the 132 LINE-1 (or L1) element ing at certain genomic loci, in line with previous reports (Kumari subfamilies in TSA- versus DMSO-treated wild-type cells (Supple- and Usdin 2001; Domcke et al. 2015). On the other hand, HDAC mental Fig. S3E; Supplemental Table S3). In DNMT.TKO cells, sig- inhibition did not have a substantial effect on the genome-wide nificant gains were detected for an additional five subfamilies occupancy of NRF1, with relatively few sites showing differential (Supplemental Fig. S3F). The most significant gains in accessibility binding upon TSA treatment in wild-type or DNMT.TKO cells in TSA-treated cells were observed at the youngest LINE-1 subfam- (Fig. 3B; Supplemental Fig. S4D). ilies (Supplemental Fig. S3G), suggesting that the presence of in- A small number of differential binding sites were identified tact transcription factor binding sites may be important in for SP1 when comparing TSA-treated or DNMT.TKO cells to wild- permitting accessibility. Among the LTR repeats, accessibility gains type cells, suggesting that this transcription factor’s occupancy is in DNMT.TKO cells predominantly occurred at ERVK-type ele- mostly unaltered by global loss of DNA methylation or genome- ments (Supplemental Fig. S3H). HDAC inhibition potentiated wide hyperacetylation alone (Fig. 3B). these gains while also increasing accessibility at some ERVL and Occupancy of GABPA, MAX, and YY1 can be modulated by ERVL-MalR-type repeats. Together, our ATAC-seq analysis indi- both DNA methylation and histone acetylation (Fig. 3B). At cates that a subset of normally methylated loci increases in acces- some binding sites, either DNA methylation or HDAC activity sibility in the absence of DNA methyltransferases, likely alone seem to be sufficient to restrict binding of these factors representing novel transcription factor binding sites. A distinct ef- (Fig. 3C; Supplemental Fig. S5A,D vs. Fig. 3D; Supplemental Fig. fect was observed upon HDAC inhibition, where the resulting ge- S5B,E), whereas at other loci the combination of both appears to nome-wide hyperacetylation led to an increase in accessibility be responsible for impeding occupancy (Fig. 3E; Supplemental outside of previously hyperaccessible sites (THSs), particularly at Fig. S5C,F). Binding sites newly acquired in DNMT.TKO cells pre- a subset of LINE elements and LTR retrotransposons. dominantly harbor the respective TF binding motifs, and these are methylated in WT cells (Fig. 4A,B). Furthermore, treatment with TSA resulted in elevated histone acetylation in the novel DNA methylation and HDAC activity can modulate transcription peaks, reinforcing the model that occupancy gains are a direct re- factor occupancy sult of chromatin perturbations (Supplemental Fig. S4E). NRF1 and NFY transcription factor motifs were enriched in THSs Although all five transcription factors predominantly occupy that appeared in DNMT.TKO cells, whereas HDAC inhibition re- gene promoter regions, the majority of ChIP-seq peaks that sulted in the appearance of THSs containing DNA sequences showed significant increases in occupancy upon DNA methyla- recognized by the AP-2 complex and TRP53 (Supplemental Figs. tion loss or HDAC inhibition were situated at promoter distal
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Cusack et al.
Figure 3. DNA methylation and HDAC activity can modulate transcription factor occupancy. (A) For each transcription factor, the position weight matrix (PWM) of its known motif and its DNA-binding domain (DBD) type are shown. (B) Pairwise comparisons of normalized GABPA, MAX, NRF1, SP1, or YY1 ChIP-seq signal for all identified occupancy peaks. Regions with significantly differential occupancy are colored on the scatterplots, and their numbers are summarized in the form of pie charts (light blue = significant decrease; red = significant increase). ChIP-seq signal from three biological replicate samples was averaged. (C–E) Representative UCSC Genome Browser snapshots showing CpG methylation levels, ATAC-seq, MAX ChIP-seq, and Input ChIP-seq read coverage.
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Figure 4. Characteristics of transcription factor (TF) binding sites. (A) Distribution of CpG methylation levels within the TF motifs that underlie ChIP-seq peaks. For each TF, we isolated all sequences that were located within peak regions that matched the relevant position weight matrix and determined the methylation status of the CpG nucleotides. CpG sites are grouped according to their differential occupancy. Black dots indicate the median. (B) Distribution of maximum log-odds scores found at different subsets of ChIP-seq peaks. Within each interval of the GABPA, MAX, NRF1, SP1, and YY1 peak-sets, the sequence most similar to the respective PWM was identified and its log-odds score, indicative of the deviation from the consensus sequence, was plotted. Black dots indicate the median. The dashed lines indicate the log-odds score threshold above which a sequence is said to match the PWM. (C) Fraction of ChIP-seq peaks that overlap an annotated transposable element. ChIP-seq peaks are classified based on their differential occupancy.
genomic sites (Supplemental Fig. S6A). The exception to this is retrotransposition, with the TF subtype being the most active in GABPA, for which TSA treatment resulted in occupancy of loci somatic cells and the germline (Akagi et al. 2008; Richardson proximal to TSSs. This is likely related to the observation that et al. 2017; Schauer et al. 2018). Of the LINE-1 elements bound TSA treatment relocates some of GABPA exclusively to nonmethy- by YY1 in TKO.TSA samples, 537 belonged to the L1Md_T subfam- lated loci (Fig. 4A), often found within CpG islands near TSSs. ily (82%) and 54 to the L1Md_Gf type (8.3%) (Supplemental Fig. We further examined whether novel intergenic ChIP-seq S6B). Both of these L1 subtypes are known to have YY1 binding peaks overlapped with transposable elements (LTRs, LINEs, and motifs in their promoter sequences that are important for retro- SINEs). Most strikingly, over half of DNMT.TKO or TSA-specific transposition (DeBerardinis and Kazazian 1999; Goodier et al. YY1 ChIP-seq peaks overlapped with transposable elements (Fig. 2001; Athanikar et al. 2004; Sanchez-Luque et al. 2019). Indeed, 4C). Particularly, 652 out of 1067 YY1 binding sites acquired in 525 of the L1Md_T and 25 of the L1Md_Gf elements that showed the absence of both DNA methylation and HDAC activity locate increased YY1 occupancy in the absence of DNA methylation and to LINE retrotransposons. Multiple LINE subfamilies exist in the HDAC activity were full-length members of their families (>5000 mouse genome that are classified by the sequence of the mono- bp and >4000 bp, respectively) and most contained at least one meric units that are tandemly repeated to make up their 5′ UTR YY1-containing monomeric units within their 5′UTR regions promoters (Goodier et al. 2001; Sookdeo et al. 2013; Zhou and (Supplemental Figs. S6C, S5E). LINE elements and particularly Smith 2019). Only full-length members of the youngest L1 sub- the L1Md_T and Gf subtypes also showed significant gains in ac- families, containing A-, TF-, or GF-type promoters are capable of cessibility in TSA-treated cells (Fig. 2G; Supplemental Table S3),
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Cusack et al. consistent with a model in which tran- A scription factor binding in the absence of HDAC activity and DNA methylation is contributing to chromatin opening. A high fraction of the YY1 binding sites acquired in DNMT.TKO cells over- lapped with LTR retrotransposons, of which 34/42 were ERVK-type elements (Fig. 4C). YY1 occupancy increases only modestly in the absence of DNA methyl- ation or following HDAC inhibition (Supplemental Fig. S6D, left panel; Sup- plemental Fig. S5F). This differs from YY1 occupancy at LINE elements, which occurs after HDAC inhibition but not as a consequence of DNA methylation loss alone (Supplemental Fig. S6D, right pan- el). In both cases, YY1 occupancy is high- est after HDAC inhibition in DNA methylation-deficient cells (Supplemen- tal Fig. S6D). Altogether, our analysis of ChIP-seq data indicates that both DNA methyla- tion and HDAC activity play distinct roles in limiting occupancy of each of the examined TFs to a fraction of their binding sites. Furthermore, we did not detect a significant loss in transcription B factor occupancy at pre-existing peaks following HDAC inhibition, whereas novel binding events were observed throughout the genome. These findings support our previous interpretation of the ATAC-seq data: that chromatin acces- sibility increases preferentially outside of established THSs and particularly at LINE and LTR retrotransposons.
Transcription factor occupancy can promote chromatin accessibility in mESCs with perturbed DNA methylation or HDAC activity We next asked whether the gains in tran- scription factor occupancy in unmethy- lated or hyperacetylated cells were directly associated with increased chro- matin accessibility. For each transcrip- tion factor, we evaluated the changes in Figure 5. Transcription factor occupancy can promote chromatin accessibility in mESCs with per- turbed DNA methylation or HDAC activity. (A) Quantitation of ATAC-seq fold change at transcription fac- ATAC-seq signal at intervals that were oc- tor ChIP-seq peaks grouped according to their differential occupancy. Black dots indicate the median cupied in one of our conditions. General- ATAC-seq fold change. One-tailed Mann–Whitney U tests; (∗) P-value <0.05, (∗∗) P-value <0.01, (∗∗∗) − ly, increased GABPA, MAX, NRF1, and P-value < 0.001, (∗∗∗∗) P-value < 10 10, (ns) nonsignificant (P-value > 0.05). (B) Percentage of ChIP-seq “ ” YY1 binding in DNMT.TKO cells was as- peaks that overlap with a Tn5 hypersensitive site (THS). In the top panel, a pre-existing THS refers to an ATAC-seq peak identified in samples generated from untreated WT cells, whereas a novel THS is iden- sociated with significant gains in accessi- tified in DNMT.TKO but not WT cells. In the bottom panel, a “pre-existing” THS was identified in samples bility (Fig. 5A, top row). Novel binding generated from untreated DNMT.TKO cells, whereas a novel THS is identified in TSA-treated DNMT.TKO events mostly occurred at sites that were cells only. previously inaccessible (Fig. 5B, top), and a few coincided with an increase in ATAC-seq signal that was sufficient to be detected as a THS. Elevat- DNMT.TKO but not WT cells (Fig. 5A, bottom two rows). Whereas ed transcription factor occupancy following HDAC treatment was HDAC inhibition led to increased occupancy of MAX, NRF1, and also associated with significant gains in accessibility, although for YY1 at predominantly inaccessible loci (i.e., that do not overlap GABPA this was only found to be the case after TSA treatment in any THS), the majority of sites to which GABPA and SP1 were
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ChromatinimpactonfunctionofTFs relocated were previously accessible (Fig. 5B, bottom). This finding repeats, we noticed that increases in accessibility that are observed is in agreement with our previous observations that all GAPBA and following HDAC inhibition but not after loss of DNA methylation half of SP1 TSA-specific binding sites occur at promoter regions were associated with significantly elevated levels of RNA originat- with low levels of DNA methylation (Fig. 4A; Supplemental Fig. ing from various subtypes (Fig. 6D; Supplemental Fig. S8A,C; S6A). Novel TF binding events that appear following HDAC inhibi- Supplemental Table S3). These included the young L1Md_T, Gf, tion are less commonly associated with increased accessibility and A subtypes for which there was also enrichment for YY1 or when compared to DNMT.TKO-specific binding events, whereas GABPA ChIP-seq reads (Fig. 6D), as well as MT2-Mm and the amplitude of change is also smaller (Fig. 5A). Although this ob- MERVL-int ERVL elements. In the case of ERVK-type repeats, loss servation might reflect a different capacity of HDAC inhibition to of DNA methylation rather than HDAC inhibition accounts for induce THSs, compared to DNA demethylation, we cannot ex- the most pronounced increases in accessibility, although this is re- clude the possibility that the lower signal is a consequence of the stricted to a subset of repeat types, including IAP elements depletion in ATAC-seq reads from THSs after treatment with TSA. (Supplemental Fig. S8B,C). However, the expression from ERVK- type elements is most strongly induced when both DNA methyla- tion and HDAC activity are abolished (comparing TKO.TSA cells to DNA methylation loss and HDAC inhibition affect the expression WT.DMSO). This observation agrees with previous reports docu- of specific genes and retrotransposons menting a synergistic activation of ERVK-type repeats in response Having established that both DNA methylation loss and HDAC in- to a combined removal of DNA methylation and HDAC activity activation can lead to changes in chromatin accessibility and tran- (Cameron et al. 1999; Coffee et al. 1999; Walter et al. 2016; scription factor occupancy, we next examined the consequences Brocks et al. 2017). for gene expression. To this aim, we performed RNA-seq using In summary, elevated transcription factor binding and ge- wild-type and DNMT.TKO cells following treatment with TSA or nome accessibility in the absence of DNA methylation or after DMSO. Loss of DNA methylation was associated with the differen- HDAC inhibition promote activation of a small subset of genes, tial expression of hundreds of genes (5.8% of total) whereas HDAC while up-regulating expression of the youngest and potentially inhibition had a more profound effect, with 20% and 27% of genes mobile LINE-1 and LTR repeats. being significantly deregulated in TSA-treated wild-type and DNMT.TKO cells, respectively (Supplemental Fig. S7A; Supple- Discussion mental Table S4). We first explored the relationship between changes in chro- In this study, we demonstrate that transcription factors have differ- matin accessibility and gene expression. We assigned each THS ent abilities to sense chromatin modifications. Even when exam- to its nearest transcription start site and examined the gene expres- ining a small number of TFs, we were able to capture distinct sion differences. We observed weak correlations between changes scenarios in which TF occupancy is affected by neither DNA mod- in chromatin accessibility and expression of the neighboring gene ifications nor histone acetylation (SP1), exclusively by DNA meth- (Spearman’s correlation coefficients for TKO.DMSO vs. ylation (NRF1), or by both (GABPA, MAX, SP1, and YY1) (Fig. 7). WT.DMSO, WT.TSA vs. WT.DMSO, or TKO.TSA vs. TKO.DMSO The total number of new binding events varies between tran- are 0.15, 0.11, and 0.10, respectively) (Fig. 6A), indicating that scription factors and does not correlate with the number of all po- most chromatin accessibility alterations are not associated with tential binding sites (i.e., sequences that match its cognate motif transcriptional changes at the closest gene. Nevertheless, more dif- perfectly). For example, in DNA methylation-deficient cells, ferentially accessible THSs show matching changes in neighboring NRF1 gains occupancy at 216 loci (increase by 0.6% of all potential gene expression than expected by chance (Fig. 6A). Many of the binding sites), whereas MAX gains occupancy at 752 (0.26%), YY1 differential THSs are promoter distal and may represent loci with – 74 (0.02%), and GABPA – 83 (0.02%) loci. Changes of a similar no regulatory function or that regulate transcriptional elements magnitude have been reported independently for another two pro- other than the closest gene. Limiting the list of THSs to those teins, MYCN and CTCF, in DNMT.TKO mES cells (Stadler et al. that are promoter proximal strengthens the correlation with 2011; Yin et al. 2017). Comprehensive in vitro experiments gene expression when comparing WT and DNMT.TKO cells but indicate that there are >100 TFs whose affinity to DNA is dimin- not TSA and control treatments (Supplemental Fig. S7B). ished by cytosine methylation (Hu et al. 2013; Yin et al. 2017). At 28 promoters, significant changes in accessibility did asso- Therefore, although the contribution of DNA methylation in re- ciate with significantly increased gene expression in DNMT.TKO stricting the occupancy of individual transcription factors appears cells (Fig. 6B,C; Supplemental Fig. S7B). These 28 genes are en- limited, the cumulative effect of DNA methylation loss on the riched for genes whose expression is normally restricted to testes gene regulatory network is likely to be more substantial. (Supplemental Table S5), fitting with a known role for DNA meth- Unlike the effect of DNA methylation depletion, HDAC inhi- ylation in controlling the expression of germ cell-specific genes bition did not result in the emergence of many discrete Tn5 hyper- (De Smet et al. 1999; Maatouk et al. 2006; Fouse et al. 2008; sensitive loci. Rather, increased chromatin accessibility was Borgel et al. 2010; Auclair et al. 2014). In conclusion, DNA meth- observed throughout the genome and particularly at a subset of ylation can restrict gene expression by maintaining an inaccessible abundant LINE and LTR transposable elements that led to a signif- chromatin state; however, the majority of gained THSs both in de- icant skew in the composition of ATAC-seq libraries. Despite ge- methylated or hyperacetylated genomes are unable to affect the nome-wide hyperacetylation, aberrant binding of the examined mRNA abundance of the nearest genes. transcription factors occurred at a scale similar to that seen follow- Considering our observations that certain subtypes of LINE-1 ing the loss of DNA methylation. Perturbations to the DNA meth- and LTR retrotransposons were selectively accessible and bound by ylation machinery or HDAC activity had distinct impacts on MAX, transcription factors following DNA methylation loss or HDAC in- GABPA, and YY1 localization both in terms of the number of aber- hibition, we turned our attention to transcription originating from rantly occupied loci as well as the genomic location of these alter- these repetitive elements. In the case of LINE-1 and ERVL-type LTR ations, indicating that DNA methylation does not depend on
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Cusack et al.
Figure 6. DNA methylation loss and HDAC inhibition affect the expression of specific genes and retrotransposons. (A) Changes in accessibility at every THS region were compared to changes in expression at their closest gene. The analysis was performed on 60052 THS:gene pairs involving 15,298 genes. The numbers of THSs associated with significant changes in both accessibility and gene expression are indicated in red in each quadrant. In parentheses are indicated the expected numbers of sites showing both significant changes in accessibility and gene expression based on the total number of significant differential events. SCC = Spearman’s correlation coefficient. (B,C) Representative UCSC Genome Browser snapshots showing CpG methylation levels, ChIP-seq, ATAC-seq, and strand-specific RNA-seq read coverage. The position of genes and that of sequences that match the TF motifs are shown. (D) For each LINE-1 subtype (N = 132), we plotted the fold change in ATAC-seq, ChIP-seq, or RNA-seq signal along with scores relating to their sequence conservation (purple) or the presence of selected TF binding motifs (green). LINE-1 subtypes were sorted based on ATAC-seq adjusted P-values when com- paring TSA- to DMSO- treated DNMT.TKO cells. See also Supplemental Table S3.
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2018). Inhibitors of HDAC and DNMT enzymes are being used for the treatment of acute myelogenous leukemia, and their use against solid tumors is being considered in combination with im- mune checkpoint inhibitors (Navada et al. 2014; West and Johnstone 2014; Daskalakis et al. 2018). In summary, we demonstrate that deacetylation of histones and DNA methylation are two important activities in chromatin, which collaborate to limit TF occupancy and contribute to silenc- ing of retrotransposon expression.
Methods Cell culture and treatment − − − − − − Dnmt1 / , Dnmt3a / , and Dnmt3b / TKO (DNMT.TKO, [Tsumura et al. 2006]) and their parental wild-type J1 male mouse embryonic stem cells (strain 129S4/SvJae) were grown on 0.1% gel- atin-coated dishes in DMEM (Lonza) complemented with 10% (v/ v) fetal bovine serum (Biosera, FB-1001G/500, lot #11484), 2 mM Figure 7. Summary model illustrating impact of DNA methylation and L-glutamine (Thermo Fisher Scientific), 1% (v/v) nonessential ami- HDAC inhibition on transcription factor occupancy. no acids (Thermo Fisher Scientific), 1% (v/v) penicillin-streptomy- cin (Thermo Fisher Scientific), 10 ng/mL leukaemia inhibitory factor (LIF, produced in-house following a protocol by Tomala HDAC activity to restrict TF occupancy in mouse ES cells. One of et al. 2010), and 0.1 mM beta-mercaptoethanol (Sigma-Aldrich). the models that is recurrently proposed to explain the transcrip- Chicken DF-1 (Doug Foster strain 1) fibroblast cells were grown tional silencing activity of DNA methylation suggests that methyl- in DMEM (Lonza) supplemented with 10% (v/v) fetal bovine se- ated CpG sequences recruit MBD-domain proteins whose rum (Biosera, FB-1001/500, lot #014BS386), 1% (v/v) penicillin- associated HDAC enzymes promote transcriptional repression streptomycin (Thermo Fisher Scientific), 2 mM L-glutamine (Eden et al. 1998; Nan et al. 1998; Kokura et al. 2001; Lyst et al. (Thermo Fisher Scientific), and 0.15% sodium bicarbonate 2013). Except for a small number of cases, the effect of HDAC in- (Thermo Fisher Scientific). All cells were incubated in a humidified hibition on chromatin accessibility, TF occupancy and gene ex- incubator set at 37°C and 5% atmospheric CO2. pression does not recapitulate that of DNA methylation loss, in HDAC inhibition in mESCs was achieved using Trichostatin A – line with similar observations in mESCs (Brunmeir et al. 2010; (TSA, Sigma-Aldrich, T1952). Cells were seeded 4 6 h prior to treat- Reichmann et al. 2012) and other cell lines (Lorincz et al. 2000; ment; once attached, their growth medium was replaced with me- Brocks et al. 2017), arguing that, at large, DNA methylation func- dium containing 5 ng/µL TSA. TSA-containing media was refreshed after 24 h, and cells were harvested for downstream ap- tions independently of HDACs. A more direct role for cytosine plications after 36 h. Control DMSO-treated cells were seeded methylation in lowering the affinity between transcription factors and treated in a similar manner; however, medium contained and their cognate DNA sequences is, however, consistent with our 0.0033% DMSO. data, as well as being supported by various biochemical and struc- tural experiments (Prendergast and Ziff 1991; Spruijt et al. 2013; Dantas Machado et al. 2015; Stephens and Poon 2016; Yin et al. Calibrated native chromatin immunoprecipitation with 2017). exogenous spike-in On the other hand, the manner by which histone deacetyla- Chicken DF-1 and mouse ES cells were harvested by trypsinization. tion hinders transcription factor binding is unclear and remains to For each experimental condition, 5 × 106 chicken DF-1 cells were be elucidated. One potential model might be that TFs are unable to added to 5 × 107 mESCs. Cell mixtures were pelleted and resus- outcompete compact chromatin, which hypoacetylated nucleo- pended in 1 ml ice-cold RSB Buffer (10 mM NaCl, 10 mM Tris somes are known to produce in vitro (Hong et al. 1993; Lee et al. [pH 8.0], 3 mM MgCl2). Chromatin was fragmented by adding 1993; Anderson et al. 2001; Shogren-Knaak et al. 2006; Wang 200 units of Micrococcal Nuclease (MNase, Fermentas) and incu- and Hayes 2008). bating at 37°C for 5 min. The reaction was stopped by the addition Although there are only a few genomic loci for which HDAC of 8 µL of 0.5 M EDTA and spun at 2348g for 5 min at 4°C. The su- inhibition or DNA methylation loss are directly responsible for al- pernatant containing soluble nucleosomes was collected (S1 frac- tion). Nucleosomes in the remaining insoluble fraction were tered TF binding and transcriptional activity, these elements are of extracted by rotating in 300 µL Nucleosome Release Buffer (10 biological and potentially clinical significance. LINEs and ERVLs, mM Tris [pH 7.5], 10 mM NaCl, 0.2 mM EDTA, with 1× for example, are reported to be essential for early embryonic devel- cOmplete EDTA-free Protease Inhibitor Cocktail [Roche] and 10 opment following fertilization (Jachowicz et al. 2017; Percharde mM sodium butyrate) for 1 h at 4°C followed by passing through et al. 2018; Kruse et al. 2019), a period during which histone acet- a 25G needle five times. The supernatant was collected as de- ylation is elevated and DNA methylation is low (Macfarlan et al. scribed above and pooled with the S1 chromatin fraction. DNA 2012; Ishiuchi et al. 2015; Eckersley-Maslin et al. 2016). fragment size was checked by agarose gel electrophoresis, indicat- Moreover, LINE mobility is observed in ES cells and is important ing that the majority of the fragments are mononucleosomal DNA in genomic diversification (Akagi et al. 2008; MacLennan et al. (150–200 bp) with a small fraction of di- and tri nucleosomal. 2017; Richardson et al. 2017). In human somatic tissues, aberrant Immunoprecipitations were set up with 100 µL solubilized L1 retrotransposition has been linked to cancer (Carreira et al. chromatin (roughly equivalent to 4 × 106 cells) and 3 µg of an anti- 2014; Tubio et al. 2014; Scott and Devine 2017; Schauer et al. acetylated histone H3 antibody (Millipore-Sigma 06-599) in a total
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Cusack et al. of 1 mL Native ChIP Incubation Buffer (10 mM Tris [pH 7.5], 70 Total RNA was depleted of ribosomal RNA using a Ribo-Zero rRNA mM NaCl, 2 mM MgCl2, 2 mM EDTA, and 0.1% Triton X-100, Removal kit (Epicentre/Illumina, Human/Mouse/Rat), and library 1× cOmplete EDTA-free Protease Inhibitor Cocktail, and 10 mM preparation was completed using the NEBNext Ultra Directional sodium butyrate) and rotated overnight at 4°C. Immune complex- RNA Library Prep kit for Illumina (New England Biolabs), both fol- es were captured using 20 µL Protein A agarose beads (Roche, pre- lowing the manufacturer’s instructions. Libraries were amplified viously saturated with 1 mg/mL BSA and 1 mg/mL yeast tRNA) for for 12 cycles. Equivalent amounts of individual libraries were 1 h at 4°C with rotation, washed four times with Native ChIP Wash pooled together. Paired-end sequencing was performed using a Buffer (20 mM Tris [pH 7.5], 2 mM EDTA, 125 mM NaCl, 0.1% HiSeq 2000 51-bp platform (v3 SBS chemistry), generating a raw Triton X-100) and once in TE buffer (10 mM Tris HCl [pH 8.0], 1 read count of >40 million reads per sample (Supplemental Table mM EDTA), and subsequently eluted in 100 µL elution buffer S1). Data analysis is provided in Supplemental Material.
(1% SDS, 0.1 M NaHCO3) by vigorous shaking for 30 min at room temperature. DNA was purified using the ZymoResearch Analysis of publicly available WGBS data ChIP DNA clean and concentrator kit (Zymo Research) following the manufacturer’s instructions. For input samples, DNA was puri- Whole-genome bisulfite sequencing data from E14 mouse ESCs (GSM1027571, Habibi et al., 2013) was analyzed using Bismark fied from 100 µL of solubilized chromatin using the same DNA pu- rification procedure. (v 0.12.5). Only cytosines with a read coverage of five or more were taken into account in this study. Material was quantified using Qubit (Invitrogen) and the size profile analyzed on the 2200 or 4200 TapeStation (Agilent, dsDNA HS Assay). Automated library preparation was performed on 5 ng Data access input material using the Apollo prep system (Wafergen, PrepX ILMN 32i, 96 sample kit) and standard Illumina multiplexing ChIP-seq, ATAC-seq, and RNA-seq sequencing data generated in adapters following the manufacturer’s protocol up to pre-PCR am- this study have been submitted to the NCBI Gene Expression plification. Libraries were PCR-amplified (18 cycles) on a Tetrad Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) under acces- (Bio-Rad) using the NEBNext High-Fidelity 2X PCR Master Mix sion number GSE131366. (NEB) and in-house single indexing primers (Lamble et al. 2013). Equivalent amounts of individual libraries were pooled. Paired- Competing interest statement end sequencing was performed using a HiSeq 4000 75-bp platform (Illumina, HiSeq 3000/4000 PE Cluster kit and 150 cycle SBS kit), The authors declare no competing interests. generating a raw read count of >30 million reads per sample (Sup- plemental Table S1). Data analysis is provided in Supplemental Material. Acknowledgments S.K. is supported by the Ludwig Institute for Cancer Research. S.K. ATAC-seq with exogenous spike-ins also acknowledges funding from the Biotechnology and Biological Sciences Research Council (BB/M001873/1) and the Conrad Assay for Transposase Accessible Chromatin (ATAC)-seq experi- N. Hilton Foundation. M.C. was funded by the Medical Research ments were carried out by adapting the protocol published by Council. We thank Masaki Okano for Dnmt TKO ESCs. We thank Buenrostro et al. (2013). Details of the sample preparation and Hiromi Tagoh, Thomas Milne, and Mary Muers for critical reading data analysis are provided in Supplemental Material. of the manuscript. Author contributions: M.C. and S.K. conceived the study and Chromatin immunoprecipitation for transcription factors wrote the manuscript with contributions from all authors; M.C. We describe the protocol for chromatin immunoprecipitation in performed all experiments and data analysis, except as indicated detail in the Supplemental Material. In brief, mouse ES cells were below; H.W.K. and M.C., under the supervision of R.J.K. and crosslinked in 1% methanol-free formaldehyde (Thermo Fisher S.K., performed ATAC-seq experiments; P.S., under the supervision Scientific) alone or sequentially with 2 mM disuccinimidyl of S.K. and B.M.K., carried out LC-MS measurements. glutarate (DSG) first, then 1% formaldehyde (YY1 only). Immuno- precipitation was carried out on sonicated chromatin using anti- References bodies listed in Supplemental Table S6. Following stringent washing, reverse crosslinking and DNA purification, libraries Akagi K, Li J, Stephens RM, Volfovsky N, Symer DE. 2008. Extensive varia- were prepared and sequenced using the same procedure as de- tion between inbred mouse strains due to endogenous L1 retrotranspo- sition. 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Distinct contributions of DNA methylation and histone acetylation to the genomic occupancy of transcription factors
Martin Cusack, Hamish W. King, Paolo Spingardi, et al.
Genome Res. published online September 22, 2020 Access the most recent version at doi:10.1101/gr.257576.119
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